Data Analyst

## About the role At Eccentric Engine, we are privileged to co-build the virtual world with some of the best minds of our time. Since 2016, we have been engaged in the Virtualisation of Automotive Retail. We have helped leading Automotive Brands in the World optimize the power of Virtual Interactions. ## Responsibilities - Collecting, cleaning, and organizing large datasets. - Developing and implementing statistical models to analyze data and uncover patterns and insights. - Building and deploying machine learning models to automate predictions and decisions. - Communicating findings and recommendations to stakeholders through visualizations, reports, and presentations. - Collaborating with cross-functional teams, such as engineering, product, and business, to drive data-driven decision making. - Ensuring the security, privacy, and ethical use of data. - Defining and tracking key performance metrics to evaluate the success of models and inform future development. - Standardize the dashboard with the help of the product manager and provide recommendations to the product manager and close the loop with the project manager/client for ad-hoc requests from the project teams. - Provide weekly product performance analysis and insights to internal and external stakeholders, keeping in mind the KPIs. - Ensure 100% data adherence for every release by working with quality assurance and provide recommendations for commissioning and decommissioning of data sets. - Monitor and analyze the performance levels of various projects and competitive products, validate changes in product/UX with data including A/B testing, and provide regular training to end-users on new reports and dashboards. - Staying up-to-date with industry trends and developments and continuously learning new data analysis and modeling techniques. ## What we seek - Forecasting, reporting, and tracking operational metrics using techniques like Moving Average, Simple Linear Regression, and Multiple Linear Regression. - Analyzing performance and usage data to create predictive models for informed decision making. - Examining past results, conducting variance analysis, identifying trends, and making recommendations for improvement. - Providing insights on trends and forecasts and suggesting actions for optimization. - Analyzing data and making comparative analyses, correlation studies, and proposing changes in methods and materials. - Identifying and improving processes, including creating standard and ad-hoc reports, tools, and Excel dashboards. - Conducting market research and data mining using techniques like Null Hypothesis, Correlation Analysis, Predictive Algorithms, and Process Stability. - Possessing proficiency in Microsoft Excel, and having familiarity with data query and management tools such as Access, SQL, and Business Objects. - Preference will be given to candidates who are well-versed in analytics tools like Google Analytics, Adobe Analytics, and Amplitude.